2017/08/31 by Nahuel Almeira, Ana Laura Schaigorodsky, Ana L. Schaigorodsky +4 · 7 citations
Computer Science · Physics and Astronomy · Social Sciences · #Complement (music) #Complex Network Analysis Techniques #Construct (python library) #Digital Games and Media #Documentation #Node (physics) #Peer-to-Peer Network Technologies #Perspective (graphical) #Popularity #Transitive relation #cs.SI #physics.soc-ph
paper · pdf · doi:10.1038/s41598-017-15428-z
published in Scientific Reports 7(1), 15186 (Nature Portfolio) · 12 pages, 6 figures, 2 tables
openalex created_date 2017/08/31 · openalex publication_date 2017/11/03 · arxiv created 2017/11/09 · arxiv updated 2017/11/10 · openalex updated_date 2026/08/05
Chess is an emblematic sport that stands out because of its age, popularity and complexity. It has served to study human behavior from the perspective of a wide number of disciplines, from cognitive skills such as memory and learning, to aspects like innovation and decision-making. Given that an extensive documentation of chess games played throughout history is available, it is possible to perform detailed and statistically significant studies about this sport. Here we use one of the most extensive chess databases in the world to construct two networks of chess players. One of the networks includes games that were played over-the-board and the other contains games played on the Internet. We study the main topological characteristics of the networks, such as degree distribution and correlations, transitivity and community structure. We complement the structural analysis by incorporating players' level of play as node metadata. Although both networks are topologically different, we show that in both cases players gather in communities according to their expertise and that an emergent rich-club structure, composed by the top-rated players, is also present.